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目的:建立化橘红中柚皮苷近红外定量模型。方法:收集不同产地不同批号化橘红样品的近红外光谱图,运用TQ Analyst 8.0软件,经一阶导数和Norris平滑预处理,在10 000~4 000 cm-1范围内,选择9个主因子数,采用偏最小二乘法(PLS)建立化橘红中柚皮苷含量近红外光定量模型。结果:所建模型预测集相关系数r=0.9927;校正集均方根偏差(RMSEC)=0.0746;预测集均方根偏差(RMSEP)=0.282;验证集预测平均回收率为101.65%(n=9)。结论:本研究所建立的模型性能较好,对化橘红中柚皮苷含量的预测准确。近红外光谱法具有快速、简便、准确、无损的优点,可以应用于化橘红药材的质量控制及其后续产品的开发。
Objective: To establish a quantitative model of Naringin in Naringin. Methods: Near infrared spectroscopy (NIRS) was used to collect samples of oranges with different batch sizes. TQ Analyst 8.0 software was used to conduct the first derivative and Norris smoothing pretreatment to select nine main factors in the range of 10,000 to 4,000 cm-1 , The partial least square method (PLS) was used to establish the quantitative model of Naringin in Naringin. Results: The correlation coefficient of prediction model set was r = 0.9927, RMSEC was 0.0746, root mean square error of prediction (RMSEP) was 0.282, and the average recovery rate of validation set was 101.65% (n = 9) ). Conclusion: The model established in this study has good performance and accurate prediction of the content of naringin in Huatan red. Near infrared spectroscopy has the advantages of fast, simple, accurate, non-destructive, can be applied to the quality control of the orange medicine and the follow-up product development.